Merge branch 'devel' of https://github.com/SumGuo-88/deepmd-kit into …

…devel

source/tests/pt/test_make_stat_input.py

@@ -69,7 +69,7 @@ def count_non_zero_elements(self, tensor, threshold=1e-8):
         return torch.sum(torch.abs(tensor) > threshold).item()
 
     def test_make_stat_input(self):
-        #3 frames would be count
+        # 3 frames would be count
         lst = make_stat_input(
             datasets=self.datasets,
             dataloaders=self.dataloaders,
@@ -87,8 +87,13 @@ def test_make_stat_input(self):
         )
 
     def test_make_stat_input_nocomplete(self):
+<<<<<<< HEAD
         #missing element:13,31,37
         #only one frame would be count
+=======
+        # missing element：13,31,37
+        # only one frame would be count
+>>>>>>> 26205d74c44201c56d39241b75e26ae381fcf67f
 
         lst = make_stat_input(
             datasets=self.datasets,
@@ -125,13 +130,11 @@ def test_bias(self):
         bias_all, _ = compute_output_stats(lst_all, ntypes=57)
         energy_ori = np.array(bias_ori.get("energy").cpu()).flatten()
         energy_all = np.array(bias_all.get("energy").cpu()).flatten()
-    
+
         for i, (e_ori, e_all) in enumerate(zip(energy_ori, energy_all)):
             if e_all == 0:
                 self.assertEqual(
-                    e_ori, 
-                    0,
-                    f"Index {i}: energy_all=0, but energy_ori={e_ori}"
+                    e_ori, 0, f"Index {i}: energy_all=0, but energy_ori={e_ori}"
                 )
             else:
                 if e_ori != 0:
@@ -140,8 +143,9 @@ def test_bias(self):
                     self.assertTrue(
                         rel_diff < 0.4,
                         f"Index {i}: energy_ori={e_ori}, energy_all={e_all}, "
-                        f"relative difference {rel_diff:.2%} is too large"
+                        f"relative difference {rel_diff:.2%} is too large",
                     )
 
+
 if __name__ == "__main__":
     unittest.main()